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检索条件"任意字段=2023 3rd International Conference on Detection Technology and Intelligence System, DTIS 2023"

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Implementation of Accident detection and Reporting system Using IOT 3

Implementation of Accident Detection and Reporting System Us...

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3rd international conference on Innovative Practices in technology and Management, ICIPTM 2023

作者： Mohandas, R. Aishwarya, V.H. Akshatha Shree, S. Anusha, S. Khushi, J. New Horizon College of Engineering Department of Electrical and Electronics Bengaluru India

ISBN: (纸本)9798350336238

The extension of transportation networks has sped up the speed of our lives. Car crashes cause a significant measure of death, property harm, and inestimable time, which is a significant worldwide medical condition. It is viewed as one of the essential executioners in the advanced world. The plan of a savvy mishap identification, area following, and cautioning framework that can detect mishaps as they happen is shrouded in this article. To find the mishap's definite area, a GPS device is utilized. The Worldwide Framework for Versatile (GSM) module sends a notification message that remembers a connection to the mishap's area for a Google guide to the nearby emergency clinic and police control focus. They can do whatever it may take to facilitate the salvage exertion by visiting the connection to find where the mishap is in the area. © 2023 IEEE.

关键词： Accidents

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cantnlp@LT-EDI-2023: Homophobia/Transphobia detection in Social Media Comments using Spatio-Temporally Retrained Language Models 3

cantnlp@LT-EDI-2023: Homophobia/Transphobia Detection in Soc...

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3rd Workshop on Language technology for Equality, Diversity and Inclusion, LTEDI 2023

作者： Wong, Sidney G.-J. Durward, Matthew Adams, Benjamin Dunn, Jonathan University of Canterbury Christchurch New Zealand

ISBN: (纸本)9789544520847

This paper describes our multiclass classification system developed as part of the LT-EDI@RANLP-2023 shared task. We used a BERT-based language model to detect homophobic and transphobic content in social media comments across five language conditions: English, Spanish, Hindi, Malayalam, and Tamil. We retrained a transformer-based cross-language pretrained language model, XLM-RoBERTa, with spatially and temporally relevant social media language data. We also retrained a subset of models with simulated script-mixed social media language data with varied performance. We developed the best performing seven-label classification system for Malayalam based on weighted macro averaged F1 score (ranked first out of six) with variable performance for other language and class-label conditions. We found the inclusion of this spatio-temporal data improved the classification performance for all language and task conditions when compared with the baseline. The results suggests that transformer-based language classification systems are sensitive to register-specific and language-specific retraining. © 2023 LTEDI 2023 - 3rd Workshop on Language technology for Equality, Diversity and Inclusion, associated with the 14th international conference on Recent Advances in Natural Language Processing, RANLP 2023 - Proceedings. All rights reserved.

关键词： Classification (of information)

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detection of Phishing Link and QR Code of UPI Transaction using Machine Learning 3

Detection of Phishing Link and QR Code of UPI Transaction us...

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3rd international conference on Innovative Mechanisms for Industry Applications, ICIMIA 2023

作者： Charan, Gangisetty Raj Thilak, K Deepa SRM Institute of Science and Technology Dept. of Networking and Communications Chennai India

ISBN: (纸本)9798350343632

Development of digital payment systems and the evolution of technology give rise to new frauds. With bogus URLs and QR Codes, phishing poses a major danger to transaction security and integrity. The proposed detection of phishing link and QR code of UPI transaction using machine learning delves into the complexity of this important topic, providing information about fraud and enhancing the exploitation of UPI ecosystems. This study intends to overcome this problem by leveraging Machine Learning and AI techniques to prevent fraud and improve security mechanisms. Phishing is a malicious attempt to pose as a reliable source in order to fool people into disclosing private information, including passwords, usernames, or bank account information. Phishing attacks can also be carried out with QR codes, which are a kind of data storage that can be swiftly accessed by a smartphone's camera. User awareness and resistance against phishing attacks. The Universal Payment Interface (UPI) is at the forefront of this disruptive wave due to its ease and efficiency in financial operations. This study investigates not just the historical context of phishing efforts but also the evolving techniques employed by fraudsters to exploit the UPI ecosystem. © 2023 IEEE.

关键词： Artificial intelligence Data Mining Football Machine Learning Predictions

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Repetition and Template Generalisability for Instance-Based Keystroke Biometric systems 3

Repetition and Template Generalisability for Instance-Based ...

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3rd IEEE international conference on Computer Communication and Artificial intelligence, CCAI 2023

作者： Parkinson, Simon Khan, Saad Liu, Na Xu, Qing University if Huddersfield Department of Computer Science Huddersfield United Kingdom University if Huddersfield Huddersfield Business School Huddersfield United Kingdom Tianjin University College of Intelligence and Computing Tianjin China

ISBN: (纸本)9798350335262

Keystroke timings can be used as a behavioural biometric, enabling passive and non-intrusive authentication. Fixed-text keystroke biometric systems involve the acquisition of keypress timings when typing a single phrase. They can be used in conjunction with a standard password authentication system to provide an increased level of security. Design decisions need to be made regarding the different technical aspects (e.g., feature sets, matching mechanism, etc.) of the system and there is a wealth of literature to guide this process. However, there is an absence of knowledge available when it comes to understanding how repetitions in user samples and characteristics of the password provided over an extended timeline can impact the system's accuracy. In this paper, timings are collected from 65 participants, who are required to type the same passwords 4 times per week for 8 weeks, yielding a total of 81,920 timing datasets. A systematic analysis is then performed for each of the 8 weeks, following the same template creation and matching process, to gain an understanding of which week's timings produce more generalised templates, providing a lower Equal Error Rate when matched against samples from all weeks. © 2023 IEEE.

关键词： Biometrics

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'AI FIT' Virtual Gym With Real-Time Exercise Form detection 3

'AI FIT' Virtual Gym With Real-Time Exercise Form Detection

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3rd international conference on Advanced Computing Technologies and Applications, ICACTA 2023

作者： Pawar, Rahul Dhake, Bhavesh Chavan, Chinmay Gohil, Unnati Ransing, Rasika Vidyalankar Institute of Technology Department of Information Technology Mumbai India

ISBN: (纸本)9798350348347

The growing importance of health and fitness in the wake of the COVID-19 pandemic has caused many people to focus on their well-being. While the fitness industry has digitalized its services, there still exists a lack of experienced human touch and a gymnasium environment in these systems. The proposed system aims to provide an integrated solution for exercise enthusiasts with all the features that can replicate an offline gym. It utilizes the process of Skeletonization using the MediaPipe library for body key point detection. It further uses a Long-term Recurrent Convolutional Network (LRCN) model composed of the Conv 2D layer and Long Short-Term Memory (LSTM) layer to detect a person's exercise form in real-time, analyse it, and display their progress in the Analysis section. With the integration of modules such as a Training Space (for understanding different exercises), Real-time Exercise Form detection, Analysis and Statistics(to provide a detailed analysis of your workout), and Blog Space(for the community to interact), this system provides a solution for exercise enthusiasts with all the features that can replicate an offline gym. The LRCN model trained on skeletonized image frames showed an accuracy of 96.49% on the train set and 95.50% on the test set for real-time form detection. © 2023 IEEE.

关键词： Gymnasiums

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Wavelet Transform-based Fault detection and ELM-based Fault Classification for Transmission Lines 3

Wavelet Transform-based Fault Detection and ELM-based Fault ...

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3rd IEEE international conference on Smart Technologies for Power, Energy and Control, STPEC 2023

作者： Tripathy, Yangyadatta Pradhan, Rudranarayan Indian Institute of Technology Roorkee Electrical Engineering Department Roorkee India Odisha University of Technology and Research School of Electrical Sciences Odisha Bhubaneswar India

ISBN: (纸本)9798350304732

This research emphasizes the necessity of fault detection and classification algorithms, specifically employing wavelet transform as a valuable tool for detecting faults that surpass predefined thresholds. The fault characteristics are extracted using Wavelet Singular Entropy (WSE) from each phase of the transmission lines. An Artificial Neural Network (ANN) is employed to classify these faults, utilizing an Extreme Learning Machine (ELM) based training algorithm. The IEEE Test 9 bus system is selected as a test case, where fault scenarios are created to conduct this study. © 2023 IEEE.

关键词： Extreme learning machines Fault Classification Fault detection Wavelet Transform

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Infrared detection technology Based on Optical Wedge Scanning 3

Infrared Detection Technology Based on Optical Wedge Scannin...

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3rd international Computing Imaging conference, CITA 2023

作者： Du, Yuping Liu, Yanyan National Key Laboratory of Electromagnetic Space Security Tianjin China

ISBN: (纸本)9781510671409

In Infrared detection system, the range of field of view is a key index to judge the system. How to detect long distance targets with large field of view by technical means on the basis of existing devices has become an urgent problem to be solved. In this paper, the imaging principle of optical wedge scanning is firstly introduced, then infrared target is used to calibrate the infrared camera, and the distortion of the scanned image is corrected by using the calibration results. Finally, the optical wedge scanning can double the imaging field of view through the semi-physical simulation. © 2023 SPIE.

关键词： Distortion Prisms Imaging systems Calibration Infrared cameras Infrared detection Image resolution Target detection Cameras Image processing

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Bio-inspired Swarm intelligence: A Flocking Project with Group Object Recognition 3

Bio-inspired Swarm Intelligence: A Flocking Project with Gro...

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3rd international conference on Consumer Electronics and Computer Engineering, ICCECE 2023

作者： Tianbo, Song Weijun, Hu Jiangfeng, Cai Weijia, Liu Quan, Yuan Kun, He Ira A. Fulton Schools of Engineering Arizona State University Tempe United States Saint Petersburg State University Faculty of Applied Mathematics and Control Processes Saint Petersburg Russia Lomonosov Moscow State University Department of Chemistry Moscow Russia Allen School of Engineering and Computing Trine University Angola United States The Open University of China Faculty of Engineering Hangzhou China College of Computing Illinois Institute of Technology Chicago United States

ISBN: (纸本)9798350331578

With the help of the adaptive gain control algorithm and the flocking SWARM algorithm with adversarial agents, the project described in this article makes the entire system communication-free while maintaining the same functionality and performance. It outlines the entirety of this biologically inspired swarm intelligence's thought process, from inception to conclusion (Flocking algorithm). The entire project is dependable and practically impenetrable under a variety of conditions. The neighbor observation for group conjecture is then strengthened by the use of the adaptive gain control technique and a partial Kalman filter. After the system has been stabilized, use the built-in camera of the SWARM drone to introduce the Object Recognition method in computer vision. As a result, the system enters the real world from the simulation level. © 2023 IEEE.

关键词： Object recognition

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Potato Plant Leaf Disease detection and Recognition Using R-CNN Model 3

Potato Plant Leaf Disease Detection and Recognition Using R-...

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3rd international conference on Pervasive Computing and Social Networking, ICPCSN 2023

作者： Balakrishnan, Minu Raja, M. Kumar, P.Vinoth Subramaniam, Suvitha Latha, R. Sri Eshwar College of Engineering Department of Information Technology Coimbatore India Cmr Institute of Technology Department of Computer Science and Engineering Bengaluru India Chennai Institute of Technology Depatment of Mechatronics Chennai India Kpr Institute of Engineering and Technology Department of English Coimbatore India Chennai India

ISBN: (纸本)9798350322842

A smart farming system that makes use of the appropriate infrastructure is an example of a new technology that aids in the improvement of the quality and quantity of the country's agricultural goods, such as potatoes. Diseases cannot be prevented since developing potato plants requires consideration of factors such as the environment, soil, and quantity of sunlight. Deep learning has resulted in recent advances in computer vision. These advancements have enabled Potato to utilize a camera to diagnose disease. This study developed an effective new method for detecting infections in potato plants. Yukon Gold, a kind of potato, served as the trial subject. Specifically, Alternaria, Blackleg, and Target Spot were targeted for detection using this method. Using 5,615 images of diseased and healthy Potato plant leaves taken in controlled environments, deep CNN is trained to identify between the presence and absence of three illnesses. To identify the Potato illnesses affecting the tracked plants, the system used a CNN. Anomaly detection using the F-RCNN-trained model achieved a confidence score of 80%, while illness identification using the Transfer Learning model achieved an accuracy of 97.85%. The effectiveness of the automated image-capturing system for diagnosing diseases in Potato plant leaves was determined to be 93.33%. © 2023 IEEE.

关键词： Convolutional neural networks

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The application of Internet of Things in intrusion detection model 3

The application of Internet of Things in intrusion detection...

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3rd international conference on Internet of Things and Smart City, IoTSC 2023

作者： Zhang, Zhiyuan Li, Xu Zhu, Chufeng Zhengzhou University Light Industry College of Mechanical and Electrical Engineering Henan Zhengzhou China

ISBN: (纸本)9781510666375

With the continuous development of 5G technology and big data processing technology, the Internet of Things has been applied to every aspect of human life. At the same time, due to the deployment of a large number of intelligent terminal equipment, massive Internet of Things traffic is generated and sent to the cloud platform storage. In the Internet of Things network environment, there are many high-dimensional, complex data characteristics. These characteristics lead to the unsatisfactory application effect of traditional intrusion detection technology in IoT security protection. Therefore, establishing a complete IoT intrusion detection system has become essential to ensuring IoT security. Since deep learning has powerful data processing and feature learning capabilities, this paper uses deep learning technology to build the Internet of Things intrusion detection model to provide the regular operation of the Internet of Things. The main research work and innovation are aimed at the problems that the sparse stack encoder (SSAE) model is challenging to learn practical features and slow convergence due to its low sparsity in dimensionality reduction of high-dimensional data in the Internet of Things. This paper improves the SSAE model and proposes a BR-SSAE model. © 2023 SPIE.

关键词： Intrusion detection

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